Yifang Liao1, Ping Li2, Yanxia Wang3, Hong Chen4, Shangwei Ning5, Dongju Su6. 1. Department of Respiratory Medicine, The 2nd Affiliated Hospital of Xiamen Medical College, Xiamen, Fujian, China. 2. Department of Radiology, The 2nd Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China. 3. College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China. 4. Department of Respiratory Medicine, The 2nd Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China. chenhong744563@aliyun.com. 5. College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China. ningsw@ems.hrbmu.edu.cn. 6. Department of Respiratory Medicine, The 2nd Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China. hydhxsdj@126.com.
Abstract
BACKGROUND: Asthma is a heterogeneous disease characterized by chronic airway inflammation. Long non-coding RNA can act as competing endogenous RNA to mRNA, and play significant role in many diseases. However, there is little known about the profiles of long non-coding RNA and the long non-coding RNA related competing endogenous RNA network in asthma. In current study, we aimed to explore the long non-coding RNA-microRNA-mRNA competing endogenous RNA network in asthma and their potential implications for therapy and prognosis. METHODS: Asthma-related gene expression profiles were downloaded from the Gene Expression Omnibus database, re-annotated with these genes and identified for asthma-associated differentially expressed mRNAs and long non-coding RNAs. The long non-coding RNA-miRNA interaction data and mRNA-miRNA interaction data were downloaded using the starBase database to construct a long non-coding RNA-miRNA-mRNA global competing endogenous RNA network and extract asthma-related differentially expressed competing endogenous RNA network. Finally, functional enrichment analysis and drug repositioning of asthma-associated differentially expressed competing endogenous RNA networks were performed to further identify key long non-coding RNAs and potential therapeutics associated with asthma. RESULTS: This study constructed an asthma-associated competing endogenous RNA network, determined 5 key long non-coding RNAs (MALAT1, MIR17HG, CASC2, MAGI2-AS3, DAPK1-IT1) and identified 8 potential new drugs (Tamoxifen, Ruxolitinib, Tretinoin, Quercetin, Dasatinib, Levocarnitine, Niflumic Acid, Glyburide). CONCLUSIONS: The results suggested that long non-coding RNA played an important role in asthma, and these novel long non-coding RNAs could be potential therapeutic target and prognostic biomarkers. At the same time, potential new drugs for asthma treatment have been discovered through drug repositioning techniques, providing a new direction for the treatment of asthma.
BACKGROUND:Asthma is a heterogeneous disease characterized by chronic airway inflammation. Long non-coding RNA can act as competing endogenous RNA to mRNA, and play significant role in many diseases. However, there is little known about the profiles of long non-coding RNA and the long non-coding RNA related competing endogenous RNA network in asthma. In current study, we aimed to explore the long non-coding RNA-microRNA-mRNA competing endogenous RNA network in asthma and their potential implications for therapy and prognosis. METHODS:Asthma-related gene expression profiles were downloaded from the Gene Expression Omnibus database, re-annotated with these genes and identified for asthma-associated differentially expressed mRNAs and long non-coding RNAs. The long non-coding RNA-miRNA interaction data and mRNA-miRNA interaction data were downloaded using the starBase database to construct a long non-coding RNA-miRNA-mRNA global competing endogenous RNA network and extract asthma-related differentially expressed competing endogenous RNA network. Finally, functional enrichment analysis and drug repositioning of asthma-associated differentially expressed competing endogenous RNA networks were performed to further identify key long non-coding RNAs and potential therapeutics associated with asthma. RESULTS: This study constructed an asthma-associated competing endogenous RNA network, determined 5 key long non-coding RNAs (MALAT1, MIR17HG, CASC2, MAGI2-AS3, DAPK1-IT1) and identified 8 potential new drugs (Tamoxifen, Ruxolitinib, Tretinoin, Quercetin, Dasatinib, Levocarnitine, Niflumic Acid, Glyburide). CONCLUSIONS: The results suggested that long non-coding RNA played an important role in asthma, and these novel long non-coding RNAs could be potential therapeutic target and prognostic biomarkers. At the same time, potential new drugs for asthma treatment have been discovered through drug repositioning techniques, providing a new direction for the treatment of asthma.
Entities:
Keywords:
Asthma; Competing endogenous RNA network; Drug repositioning; Long non-coding RNA; mRNA
Authors: Alvin T Kho; Michael J McGeachie; Jiang Li; Robert P Chase; Sami S Amr; Annette T Hastie; Gregory A Hawkins; Xingnan Li; Geoffrey L Chupp; Deborah A Meyers; Eugene R Bleecker; Scott T Weiss; Kelan G Tantisira Journal: Thorax Date: 2021-09-27 Impact factor: 9.102